code: def training_step(self, batch, batch_idx):
      x, y = batch
      y_hat = self(x)
      loss = F.binary_cross_entropy_with_logits(
          y_hat.flatten(), y.float()
      )
  
      # The metrics below will be reported to Loggers
      self.log("train_loss", loss)
      self.log_dict(
          {"metric_1": 1 / (batch_idx + 1), "metric_2": batch_idx * 100}
      )
      return loss
  
file_path: ray/python/ray/train/examples/experiment_tracking/lightning_exp_tracking_model_dl.py
imports: import pytorch_lightning
  import torch
  import torch.nn.functional
  from torch.utils.data import DataLoader, TensorDataset
label_desc: Use image node_id 3 for calling the DummyModel obj's underlying member method code with example usage: obj.training_step(batch, batch_idx) and returns: loss